A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision

In this manuscript, we describe a unique dataset of human locomotion captured in a variety of out-of-the-laboratory environments captured using Inertial Measurement Unit (IMU) based wearable motion capture. The data contain full-body kinematics for walking, with and without stops, stair ambulation,...

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Bibliographic Details
Published in:Scientific data 2023-01, Vol.10 (1), p.26-11, Article 26
Main Authors: Sharma, Abhishek, Rai, Vijeth, Calvert, Melissa, Dai, Zhongyi, Guo, Zhenghao, Boe, David, Rombokas, Eric
Format: Article
Language:English
Subjects:
631/114/1305
639/166/985
639/166/988
639/705/1046
692/700/478
Biomechanical Phenomena
Classrooms
Computer engineering
Data Descriptor
Datasets
Experiments
Female
Gait
Humanities and Social Sciences
Humans
Kinematics
Laboratories
Locomotion
Male
Motion capture
multidisciplinary
Public spaces
Science
Science (multidisciplinary)
Walking
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Description
Summary:In this manuscript, we describe a unique dataset of human locomotion captured in a variety of out-of-the-laboratory environments captured using Inertial Measurement Unit (IMU) based wearable motion capture. The data contain full-body kinematics for walking, with and without stops, stair ambulation, obstacle course navigation, dynamic movements intended to test agility, and negotiating common obstacles in public spaces such as chairs. The dataset contains 24.2 total hours of movement data from a college student population with an approximately equal split of males to females. In addition, for one of the activities, we captured the egocentric field of view and gaze of the subjects using an eye tracker. Finally, we provide some examples of applications using the dataset and discuss how it might open possibilities for new studies in human gait analysis.
ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-023-01932-7